Applying configurational analysis to IS behavioural research: a methodological alternative for modelling combinatorial complexities

Abstract

An important limitation of regression-based analysis stems from the assumption of symmetric relationships between variables, which is often violated. To overcome this limitation within IS research, we propose the use of the fuzzy-set qualitative comparative analysis (FsQCA) method. The paper elaborates on the rationale for applying this approach to IS behavioural research and how to tailor FsQCA for this purpose. A systematic interpretation of the technique covering its mathematical properties and advanced features is provided. Drawing from an illustrative study of mobile government services adoption by residents of rural areas, the paper demonstrates FsQCA's potential to supplement regression-based IS behavioural research, by (i) examining asymmetric relationships between a set of antecedents and the IS phenomenon of interest, (ii) providing nuanced coverage of necessary and sufficient conditions for emergence of an IS behavioural outcome, and (iii) identifying various configurations of conditions in association with users' demographic characteristics.

Explaining travellers online information satisfaction: A complexity theory approach on information needs, barriers, sources and personal characteristics

“…Specifically, we employ configurational analysis to examine asymmetric relationships among the constituents of the online information search process. This approach has recently received scholars' attention in the Information Systems discipline [79], and coupled with complexity theory, it may help in theory building [80]. Extant studies on the antecedents of satisfaction in online travel-related information seeking focus on the average effects of single variables rather than on the effects of combinations (sets) of several variables [11,16,20,27,35,70,81].…”

Assessing Student Behavior in Computer Science Education with an fsQCA Approach

“…All are built on the same few rules" [Lewin 1992, back cover]. We expand on the contributions of other studies from the areas of sociology [Ragin 2008], business management [Pappas et al 2017], information systems [Liu et al, 2015] and others.…”

“…fsQCA was developed by integrating fuzzy set and fuzzy logic [Zadeh 1965] with QCA [Ragin, 2000]. Fuzzy sets and fuzzy logic principles apply in engineering and control theory, as well as in social sciences [Liu et al 2015]. fsQCA identifies patterns between independent and dependent variables, which leads to outcomes and goes a step further from analyses of variance, correlations and multiple regression models.…”

Minimizing Complementors Risk in Third-Party Innovation: A Qualitative Comparative Analysis (QCA) of Digital Platform Configurations

“…On the other hand, recent organizational [14] and information systems research [25] suggests that the assumption of symmetric causal relationships might not adequately display organizational realities [13]. In contrast, configurational theories imply equifinality between different sets of initial conditions [33] and assume asymmetric rather than symmetric relations between conditional variables and outcomes [13].…”